DocumentCode :
693945
Title :
Coal Demand Forecast Based on Consumption Structure Partition
Author :
Zhongyu Zhang ; Jian Chai ; Qing Zhu
Author_Institution :
Int. Bus. Sch., Shaanxi Normal Univ., Xi´an, China
fYear :
2013
fDate :
14-16 Nov. 2013
Firstpage :
485
Lastpage :
489
Abstract :
In order to forecast total coal demand of China, this paper divides consumption by sector in detail, including Agriculture, Forestry, Animal Husbandry, Fishery and Water Conservancy, Industry, Construction, Transport, Storage and Post, Wholesale and Retail Trades, Hotels and Catering Services, Other Sectors, Household Consumption. Then, this paper forecasts coal consumption value until next decade by collecting 1980-2010 coal consumption data and choosing ETS and Holt-Winters forecasting models from multitudinous models. At the same time, combining with the historical data and predicted results, different trends of total and proportion of coal consumption has carried on the detailed analysis and explanation of each sector. Finally, total coal consumption forecast value is obtained by combining the results of two univariate forecasting models. Empirical results show that by 2020, total coal demand is 4.7 billion tons of china. Therefore, the implementation of energy conservation and emissions reduction, improvement of energy efficiency, development of new energy and other measures are more help ensure the sustainable development of China.
Keywords :
air pollution; coal; demand forecasting; energy conservation; sustainable development; China; ETS; Holt-Winters forecasting model; coal consumption data; emission reduction; energy conservation; energy development; energy efficiency; historical data; multitudinous models; sustainable development; total coal consumption forecast value; total coal demand forecasting; univariate forecasting models; Biological system modeling; Coal; Data models; Forecasting; Industries; Market research; Predictive models; ETS; Holt-Winters; coal demand; combination forecast; consumption structure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Business Intelligence and Financial Engineering (BIFE), 2013 Sixth International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-4778-2
Type :
conf
DOI :
10.1109/BIFE.2013.102
Filename :
6961183
Link To Document :
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